Channel exit morphology is a critical structural feature of Hall thrusters, influencing their performance and longevity. A three-dimensional point cloud model of the channel exit morphology is constructed using binocular structured light scanning, integrated with a mechanical positioning system. The purpose is to enable in situ inspection within a vacuum chamber. The channel exit wall diameter and the radius of the rounded edge are extracted using a combination of radius-based filtering, density-based spatial clustering of applications with noise, and curvature-based feature extraction. In addition, least squares fitting is applied to refine the measurements. The accuracy of the proposed method is validated through experiments. The results indicate that the maximum error is 43 μm compared to the coordinate measuring machine, which meets the required threshold of 50 μm. This non-contact, automated approach offers a promising alternative to traditional inspection methods. It significantly improves the efficiency of the testing process by supporting in situ evaluation of the Hall thruster channel exit.
Tong et al. (Sun,) studied this question.
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